matplotlib scatter plot colour as function of third variable [duplicate]
This works for me, using matplotlib 1.1:
import numpy as npimport matplotlib.pyplot as pltx = np.arange(10)y = np.sin(x)plt.scatter(x, y, marker='+', s=150, linewidths=4, c=y, cmap=plt.cm.coolwarm)plt.show()
Result:
Alternatively, for n points, make an array of RGB color values with shape (n, 3), and assign it to the edgecolors
keyword argument of scatter()
:
import numpy as npimport matplotlib.pyplot as pltx = np.linspace(0, 20, 100)y = np.sin(x)z = x + 20 * yscaled_z = (z - z.min()) / z.ptp()colors = plt.cm.coolwarm(scaled_z)plt.scatter(x, y, marker='+', edgecolors=colors, s=150, linewidths=4)plt.show()
Result:
That example gets the RGBA values by scaling the z
values to the range [0,1], and calling the colormap plt.cm.coolwarm
with the scaled values. When called this way, a matplotlib colormap returns an array of RGBA values, with each row giving the color of the corresponding input value. For example:
>>> t = np.linspace(0, 1, 5)>>> tarray([ 0. , 0.25, 0.5 , 0.75, 1. ])>>> plt.cm.coolwarm(t) array([[ 0.2298, 0.2987, 0.7537, 1. ], [ 0.5543, 0.6901, 0.9955, 1. ], [ 0.8674, 0.8644, 0.8626, 1. ], [ 0.9567, 0.598 , 0.4773, 1. ], [ 0.7057, 0.0156, 0.1502, 1. ]])